This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (120) Artificial Intelligence (2314) Imaging Informatics (325)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47445, first published .
Artificial Intelligence–Based Methods for Integrating Local and Global Features for Brain Cancer Imaging: Scoping Review

Artificial Intelligence–Based Methods for Integrating Local and Global Features for Brain Cancer Imaging: Scoping Review

Artificial Intelligence–Based Methods for Integrating Local and Global Features for Brain Cancer Imaging: Scoping Review

Authors of this article:

Hazrat Ali1 Author Orcid Image ;   Rizwan Qureshi2 Author Orcid Image ;   Zubair Shah1 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Xu Z, Wang Z. MCV-UNet: a modified convolution & transformer hybrid encoder-decoder network with multi-scale information fusion for ultrasound image semantic segmentation. PeerJ Computer Science 2024;10:e2146 View
  2. Rojek I, Mikołajewski D, Dorożyński J, Dostatni E, Mreła A. An ML-Based Solution in the Transformation towards a Sustainable Smart City. Applied Sciences 2024;14(18):8288 View

Conference Proceedings

  1. Maulana F, Fauzya S, Ardiyanto I, Nugroho H. 2025 5th International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA). Integrated 3D Lung Cancer Analysis with Evaluation of ViT-Based Architectures for Segmentation View